EVOLUTION-MANAGER

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Multiple QTL Mapping (MQM) provides a sensitive approach for mapping quantititive trait loci (QTL) in experimental populations. MQM adds higher statistical power compared to many other methods. The theoretical framework of MQM was introduced and explored by Ritsert Jansen, explained in the `Handbook of Statistical Genetics' (see references), and used effectively in practical research, with the commercial `mapqtl' software package. Here we present the first free and open source implementation of MQM, with extra features like high performance parallelization on multi-CPU computers, new plots and significance testing. MQM is an automatic three-stage procedure in which, in the first stage, missing data is `augmented'. In other words, rather than guessing one likely genotype, multiple genotypes are modeled with their estimated probabilities. In the second stage important markers are selected by multiple regression and backward elimination. In the third stage a QTL is moved along the chromosomes using these pre-selected markers as cofactors, except for the markers in the window around the interval under study. QTL are (interval) mapped using the most `informative' model through maximum likelihood. A refined and automated procedure for cases with large numbers of marker cofactors is included. The method internally controls false discovery rates (FDR) and lets users test different QTL models by elimination of non-significant cofactors.